Data Analytics AI Use Case AI Strategy

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Est. reading time: 4 minutes
Author: Steph Organ

There’s no doubt that going ahead with Artificial Intelligence (AI) can be risky. We’ve seen numerous AI fails from major companies including IBM, Amazon and Microsoft which landed them in hot water, something big companies can often bounce back from, but could be more of a problem for the smaller players. The trick to getting started with AI is to start small, which is where our quick win AI projects come into play.

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Steph Organ

Ambitious digital marketer with a love for words and history of content creation.

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There’s no doubt that going ahead with Artificial Intelligence (AI) can be risky. We’ve seen numerous AI fails from major companies including IBM, Amazon and Microsoft which landed them in hot water, something big companies can often bounce back from, but could be more of a problem for the smaller players. The trick to getting started with AI is to start small, which is where our quick win AI projects come into play.

With a quick win project, you can build up confidence around taking on AI within your organisation while simultaneously showing off the immediate value and benefits of engaging with it, as we previously discussed with AI for sales processes or knowledge worker productivity, and today with Intelligent Insights.

A bit about BI

Business Intelligence (BI) has long been an important tool for visualising business data, giving important insights that aid decision making. In its prime, BI was revolutionary. With the rise and evolution of computers, BI became more fine-tuned and accessible as big players like IBM entered the game and BI providers came to the market. For the first time, organisations were able to collect data and act on insights producing significant results.

BI evolved further as the costs of storing data lowered and new tools were developed to streamline access, but at this point, AI and Machine Learning (ML) techniques were on the rise, and now AI is the new BI. That is not to say that Artificial Intelligence techniques have replaced BI, we just mean that that now it is important to use AI-infused BI tools in order to gain intelligent insights and move from reactive to proactive insights.

The value

Why isn’t BI enough? Sure, BI can deliver descriptive, predictive and even prescriptive analytics, but modern businesses need more. With so much data coming in, a sea of dashboards and data won’t suffice, companies need to be able to extract the relevant insights. But AI features like Natural Language Processing (NLP) can mean added features like Power BI’s Q&A which allows you to request data insights just by typing a question or even interacting through Siri.

Thanks to cloud computing, AI-infused BI tools can allow you to view these insights in realtime, and they can allow you to dig deeper. The Key Influencers Visuals in PowerBI lets you see the factors that may have influenced the results, giving a better understanding of why things are the way they are.

AI integrations such as language detection, key phrase extraction, imaging tagging and sentiment scoring can help you gain insights from unstructured data or from a variety of sources, helping you to see the bigger picture. AI can simplify the use of analytic tools meaning that people across all departments can access data more easily and use it to make data-driven decisions, not just your data experts.

The project

To start generating intelligent insights, you first need to choose your AI-infused BI tool. Some popular options include Power BI, ThoughtSpot and Tablaeu but there are many more with ranging prices to suit different needs. To start using your tool you then need to identify your data sources and decide what you want to learn from it. AI tools will be able to help user extract insights from a sea of data, but it still helps to set out with a purpose, otherwise, your insights will be random and have little value, rather than solving a problem.

Once you have selected the source and insight you wish to gain from your data, it is time to visualise it. Build relevant dashboards to view your data so that you can denitrify trends and patterns and make powerful business decisions.

It may be necessary to offer some training around using the tool to keep everyone on your team up to speed with how to extract insights and help to feed a healthy data culture and standardise data practices across your team. For training around data and AI capabilities, check out our courses or get in touch with us to request a tailored course for your staff.

More quick wins

It can be that easy to infuse AI into decision-making processes and only takes a little adjustment to get your whole team data-savvy. If you’re interested in more ways to infuse your work processes with AI, download our free 7 Quick Wins Projects guide.

Improve operations

Get quick-win projects done

Speak with our AI specialists